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An Eigenvector Approach for Analysing Linear Feedback Systems

机译:特征向量法分析线性反馈系统

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Formal analysis plays an important role in understanding how feedback structures drive dx-namical behaviour. As we know the state behaviour is determined by a linear combination of behaviour modes (associated with eigenvalues). The weight of each mode is a product of a coefficient and a right eigenvector component. An emerging technique in eigen-based analysis focuses on the behaviour mode weight, together with the behaviour mode (eigenvalue), to identify the dominant feedback structure. The purpose of incorporating the weight analysis is to conduct an overall assessment of how feedback structure influences on the state behaviour. This paper revises the conventional eigensolution to the state trajectory by alternating the behaviour mode coefficient to be a product of the normalized left eigenvector, and the system initial conditions. Therefore, the overall behaviour changes due to the changes in a system element (a link or a pathway) can be fully assessed by calculating the eigenvalue, right and left eigenvector sensitivities. Through studying the eigenvector sensitivity, we observe that the right and left eigenvector sensitivities associated with the same mode cannot be evaluated separately. We present an analytical approach to the eigenvector-related sensitivity computation, i.e., a linear combination of the right and left eigenvector sensitivity.
机译:形式分析在理解反馈结构如何驱动dx行为方面起着重要作用。众所周知,状态行为是由行为模式(与特征值相关)的线性组合决定的。每个模式的权重是系数和右特征向量分量的乘积。基于本征分析的一种新兴技术着眼于行为模式权重以及行为模式(特征值),以识别主导反馈结构。合并权重分析的目的是对反馈结构如何影响状态行为进行总体评估。通过将行为模式系数作为归一化左特征向量和系统初始条件的乘积,本文将传统的本征解修改为状态轨迹。因此,可以通过计算特征值,左右特征向量敏感度来完全评估由于系统元素(链接或路径)的变化而引起的总体行为变化。通过研究特征向量敏感度,我们观察到与同一模式相关的左右特征向量敏感度无法单独评估。我们提出了一种与特征向量相关的灵敏度计算的分析方法,即左右特征向量灵敏度的线性组合。

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